U.S. patent application number 14/972981 was filed with the patent office on 2017-06-22 for system and method for controlling wind turbines.
The applicant listed for this patent is General Electric Company. Invention is credited to Carlo Luigi Bottasso, Stefano Cacciola, Fabiano Daher Adegas, Sara Simonne L. Delport.
Application Number | 20170175709 14/972981 |
Document ID | / |
Family ID | 59065048 |
Filed Date | 2017-06-22 |
United States Patent
Application |
20170175709 |
Kind Code |
A1 |
Daher Adegas; Fabiano ; et
al. |
June 22, 2017 |
SYSTEM AND METHOD FOR CONTROLLING WIND TURBINES
Abstract
A control system for a wind turbine is provided. The wind
turbine includes at least one stationary component. The control
system includes at least one mechanical load measurement sensor
coupled to the at least one stationary component. The system also
includes at least one modeling device configured to generate and
transmit at least one wind turbine regulation device command signal
to at least one wind turbine regulation device to regulate
operation of the wind turbine based upon at least one wind inflow
parameter.
Inventors: |
Daher Adegas; Fabiano;
(Munich, DE) ; Delport; Sara Simonne L.; (Munich,
DE) ; Bottasso; Carlo Luigi; (Monza, IT) ;
Cacciola; Stefano; (Gorgonzola, IT) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
General Electric Company |
Schenectady |
NY |
US |
|
|
Family ID: |
59065048 |
Appl. No.: |
14/972981 |
Filed: |
December 17, 2015 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
F05B 2270/331 20130101;
F05B 2270/101 20130101; F03D 7/045 20130101; F05B 2270/304
20130101; F03D 7/048 20130101; F03D 7/047 20130101; Y02E 10/723
20130101; F05B 2240/60 20130101; F05B 2220/30 20130101; F05B
2270/32 20130101; Y02E 10/721 20130101; F03D 7/0224 20130101 |
International
Class: |
F03D 7/04 20060101
F03D007/04; F03D 80/70 20060101 F03D080/70; F03D 13/20 20060101
F03D013/20; F03D 17/00 20060101 F03D017/00; F03D 7/02 20060101
F03D007/02; F03D 1/06 20060101 F03D001/06 |
Claims
1. A control system for a wind turbine, the wind turbine including
at least one stationary component, said control system comprising:
at least one mechanical load measurement sensor coupled to the at
least one stationary component; at least one wind turbine
regulation device configured to regulate operation of the wind
turbine as a function of at least one wind inflow parameter; and at
least one modeling device coupled to said at least one mechanical
load measurement sensor and said at least one wind turbine
regulation device, said at least one modeling device configured to:
receive at least one mechanical load measurement signal from said
at least one mechanical load measurement sensor coupled to the at
least one stationary component; generate the at least one wind
inflow parameter based on the at least one mechanical load
measurement signal; generate at least one wind turbine regulation
device command signal based on the at least one wind inflow
parameter; and transmit the at least one wind turbine regulation
device command signal to said at least one wind turbine regulation
device to regulate operation of the wind turbine.
2. The control system in accordance with claim 1, wherein the wind
turbine includes a rotor, a rotor hub coupled to the rotor, a
plurality of wind turbine blades coupled to the rotor hub, a shaft
flange coupled to the rotor, a tower, a main bearing housing, and a
yaw bearing, wherein said at least one mechanical load measurement
sensor is coupled to one or more of the shaft flange, the rotor
hub, the rotor shaft, the main bearing housing, and the yaw
bearing.
3. The control system in accordance with claim 1, wherein said
control system further comprises at least one wind turbine
operational data sensor coupled to said at least one modeling
device, said at least one modeling device further configured to:
receive at least one wind turbine operational data signal from said
at least one wind turbine operational data sensor; and generate the
at least one wind inflow parameter based on the at least one wind
turbine operational data signal.
4. The control system in accordance with claim 1, wherein said
control system further comprises at least one blade pitch angle
sensor coupled to said at least one modeling device, said at least
one modeling device further configured to: receive at least one
blade pitch angle signal from said at least one blade pitch angle
sensor; and generate the at least one wind inflow parameter based
on the at least one blade pitch angle signal.
5. The control system in accordance with claim 1, wherein said
control system further comprises at least one atmospheric condition
measurement sensor coupled to said at least one modeling device,
said at least one modeling device further configured to: receive at
least one atmospheric condition measurement signal from said at
least one atmospheric condition measurement sensor; and generate
the at least one wind inflow parameter based on the at least one
atmospheric condition measurement signal.
6. The control system in accordance with claim 1, wherein the wind
turbine includes a shaft flange, said at least one mechanical load
measurement sensor configured to measure displacement of the shaft
flange.
7. The control system in accordance with claim 1, wherein the wind
turbine includes a shaft flange, said at least one mechanical load
measurement sensor configured to measure a strain of the shaft
flange.
8. The control system in accordance with claim 1, wherein the wind
turbine includes a tower and a tower top, said at least one
mechanical load measurement sensor configured to measure bending of
the tower top.
9. The control system in accordance with claim 1, wherein said at
least one modeling device is further configured to generate, based
upon the at least one mechanical load measurement signal, one or
more estimates of wind inflow parameters, including, but not
limited to, yaw misalignment, up-flow, vertical shear, horizontal
shear, wind profile, veer, turbulence intensity, a waked state, and
a non-waked state.
10. A method for controlling a wind turbine, the wind turbine
including at least one stationary component, at least one
mechanical load measurement sensor coupled to the at least one
stationary component, at least one wind turbine regulation device,
and at least one modeling device coupled to the at least one
mechanical load measurement sensor and the at least one wind
turbine regulation device, said method comprising: receiving, by
the modeling device, at least one mechanical load measurement
signal from the at least one mechanical load measurement sensor;
generating, by the modeling device, at least one wind inflow
parameter based on the at least one mechanical load measurement
signal; generating, by the modeling device, at least one wind
turbine regulation device command signal based on the at least one
wind inflow parameter; and transmitting, by the modeling device,
the at least one wind turbine regulation device command signal to
the at least one wind turbine regulation device to regulate
operation of the wind turbine.
11. The method in accordance with claim 10, wherein the wind
turbine includes a rotor, a rotor hub coupled to the rotor, a
plurality of wind turbine blades coupled to the rotor hub, a shaft
flange coupled to the rotor, a tower, a main bearing housing, and a
yaw bearing, wherein the at least one mechanical load measurement
sensor is coupled to one or more of the shaft flange, the rotor
hub, the rotor shaft, the main bearing housing, and the yaw
bearing.
12. The method in accordance with claim 10, wherein the at least
one modeling device is coupled to at least one wind turbine
operational data sensor, said method further comprising: receiving,
by the modeling device, at least one wind turbine operational data
signal from the at least one wind turbine operational data sensor;
and generating, by the modeling device, the at least one wind
inflow parameter based on the at least one wind turbine operational
data signal.
13. The method in accordance with claim 10, wherein the at least
one modeling device is coupled to at least one blade pitch angle
sensor, said method further comprising: receiving, by the modeling
device, at least one blade pitch angle signal from the at least one
blade pitch angle sensor; and generating, by the modeling device,
the at least one wind inflow parameter based on the at least one
blade pitch angle signal.
14. The method in accordance with claim 10, wherein the at least
one modeling device is coupled to at least one atmospheric
condition measurement sensor, said method further comprising:
receiving, by the modeling device, at least one atmospheric
condition measurement signal from the at least one atmospheric
condition measurement sensor; and generating, by the modeling
device, the at least one wind inflow parameter based on the at
least one atmospheric condition measurement signal.
15. The method in accordance with claim 10, further comprising
generating, by the modeling device, based upon the at least one
mechanical load measurement signal, one or more estimates of wind
inflow parameters, including, but not limited to, yaw misalignment,
up-flow, vertical shear, horizontal shear, wind profile, veer,
turbulence intensity, a waked state, and a non-waked state.
16. A wind turbine park comprising: a plurality of wind turbines
comprising an operating wind turbine, wherein at least one wind
turbine includes at least one stationary component; at least one
mechanical load measurement sensor coupled to the at least one
stationary component; at least one wind turbine regulation device
configured to regulate operation of the at least one wind turbine
as a function of at least one wind inflow parameter; and at least
one modeling device coupled to said at least one mechanical load
measurement sensor and said at least one wind turbine regulation
device, said at least one modeling device configured to: receive at
least one mechanical load measurement signal from said at least one
mechanical load measurement sensor; generate the at least one wind
inflow parameter based on the at least one mechanical load
measurement signal; generate at least one wind turbine regulation
device command signal based on the at least one wind inflow
parameter; and transmit the at least one wind turbine regulation
device command signal to said at least one wind turbine regulation
device to regulate operation of said wind turbine park.
17. The wind turbine park in accordance with claim 16, wherein said
wind turbine park further comprises at least one wind turbine
operational data sensor coupled to said at least one modeling
device, said at least one modeling device further configured to:
receive at least one wind turbine operational data signal from said
at least one wind turbine operational data sensor; and generate the
at least one wind inflow parameter based on the at least one wind
turbine operational data signal.
18. The wind turbine park in accordance with claim 16, wherein said
wind turbine park further comprises at least one blade pitch angle
sensor coupled to said at least one modeling device, said at least
one modeling device further configured to: receive at least one
blade pitch angle signal from said at least one blade pitch angle
sensor; and generate the at least one wind inflow parameter based
on the at least one blade pitch angle signal.
19. The wind turbine park in accordance with claim 16, wherein said
wind turbine park further comprises at least one atmospheric
condition measurement sensor coupled to said at least one modeling
device, said at least one modeling device further configured to:
receive at least one atmospheric condition measurement signal from
said at least one atmospheric condition measurement sensor; and
generate the at least one wind inflow parameter based on the at
least one atmospheric condition measurement signal.
20. The wind turbine park in accordance with claim 16, wherein the
at least one wind turbine includes a rotor, a rotor hub coupled to
the rotor, a plurality of wind turbine blades coupled to the rotor
hub, a shaft flange coupled to the rotor, a tower, a main bearing
housing, and a yaw bearing, wherein said at least one mechanical
load measurement sensor is coupled to one or more of the shaft
flange, the rotor hub, the rotor shaft, the main bearing housing,
and the yaw bearing.
21. The wind turbine park in accordance with claim 16, wherein said
modeling device is further configured to generate, based upon the
at least one mechanical load measurement signal, one or more
estimates of wind inflow parameters, including, but not limited to,
yaw misalignment, up-flow, vertical shear, horizontal shear, wind
profile, veer, turbulence intensity, a waked state, and a non-waked
state.
Description
BACKGROUND
[0001] The field of the disclosure relates to wind turbines, and
more particularly to a system and method for controlling wind
turbines based upon mechanical load measurements and wind turbine
operational data.
[0002] Most known wind turbine generators include a rotor having
multiple blades. The rotor is sometimes coupled to a housing, or
nacelle, that is positioned on top of a base, for example, a
tubular tower. At least some known utility grade wind turbines,
i.e., wind turbines designed to provide electrical power to a
utility grid have rotor blades having predetermined shapes and
dimensions. The rotor blades transform kinetic wind energy into
induced blade aerodynamic forces that further induce a mechanical
rotational torque that drives one or more generators, subsequently
generating electric power. A plurality of wind turbine generators
in a localized geographic array is typically referred to as a wind
farm or a wind park.
[0003] Wind turbines are exposed to large variations in wind
inflow, which exerts varying loads to the wind turbine structure,
particularly the wind turbine rotor and shaft. Real-time estimates
of wind inflow conditions on a wind turbine can be used to control
the wind turbine to increase power performance and annual energy
production and reduce mechanical loads. The inflow estimates can,
for example, be used to predict turbine wake length and strength
with greater accuracy, enabling better turbine control and
increased power performance. Real-time estimates of the wind inflow
conditions can also be used to reduce wind turbine noise and
increase the accuracy in predicting wind turbine noise under
different inflow conditions. The ability to estimate noise emission
with greater accuracy allows wind turbines to more closely
approach, but not exceed, the noise limitations imposed by
regulations.
[0004] Known approaches have been employed to address the issue of
measuring wind inflow conditions on a wind turbine. One such
approach is to deduce wind inflow conditions by using rotor blade
sensors to measure flow properties proximate to the surface of each
rotor blade. Another approach is to use LiDAR sensors installed on
the turbine rotor blades, spinner, or nacelle. However, these
sensors are costly and their performance is subject to weather
conditions.
BRIEF DESCRIPTION
[0005] In one aspect, a control system for a wind turbine is
provided. The wind turbine includes at least one stationary
component. The control system includes at least one mechanical load
measurement sensor coupled to the at least one stationary
component. The control system further includes at least one wind
turbine regulation device configured to regulate operation of the
wind turbine as a function of at least one wind inflow parameter.
The control system also includes at least one modeling device
coupled to the at least one mechanical load measurement sensor and
the at least one wind turbine regulation device. The at least one
modeling device is configured to receive at least one mechanical
load measurement signal from the at least one mechanical load
measurement sensor coupled to the at least one stationary
component. The at least one modeling device is further configured
to generate the at least one wind inflow parameter based on the at
least one mechanical load measurement signal. The at least one
modeling device is also configured to generate at least one wind
turbine regulation device command signal based on the at least one
wind inflow parameter. The at least one modeling device is further
configured to transmit the at least one wind turbine regulation
device command signal to the at least one wind turbine regulation
device to regulate operation of the wind turbine.
[0006] In another aspect, a method for controlling a wind turbine
is provided. The wind turbine includes at least one stationary
component. The wind turbine further includes at least one
mechanical load measurement sensor coupled to the at least one
stationary component. The wind turbine also includes at least one
wind turbine regulation device. The wind turbine further includes
at least one modeling device coupled to the at least one mechanical
load measurement sensor and the at least one wind turbine
regulation device. The method includes receiving, by the modeling
device, at least one mechanical load measurement signal from the at
least one mechanical load measurement sensor. The method further
includes generating, by the modeling device, at least one wind
inflow parameter based on the at least one mechanical load
measurement signal. The method also includes generating, by the
modeling device, at least one wind turbine regulation device
command signal based on the at least one wind inflow parameter. The
method further includes transmitting, by the modeling device, the
at least one wind turbine regulation device command signal to the
at least one wind turbine regulation device to regulate operation
of the wind turbine.
[0007] In a further aspect, a wind turbine park is provided. The
wind turbine park includes a plurality of wind turbines including
an operating wind turbine. At least one wind turbine includes at
least one stationary component. The at least one wind turbine
further includes at least one mechanical load measurement sensor
coupled to the at least one stationary component. The at least one
wind turbine also includes at least one wind turbine regulation
device configured to regulate operation of the at least one wind
turbine as a function of at least one wind inflow parameter. The at
least one wind turbine further includes at least one modeling
device coupled to the at least one mechanical load measurement
sensor and the at least one wind turbine regulation device. The at
least one modeling device is configured to receive at least one
mechanical load measurement signal from the at least one mechanical
load measurement sensor. The at least one modeling device is
further configured to generate the at least one wind inflow
parameter based on the at least one mechanical load measurement
signal. The at least one modeling device is also configured to
generate at least one wind turbine regulation device command signal
based on the at least one wind inflow parameter. The at least one
modeling device is further configured to transmit the at least one
wind turbine regulation device command signal to the at least one
wind turbine regulation device to regulate operation of the wind
turbine park.
DRAWINGS
[0008] These and other features, aspects, and advantages of the
present disclosure will become better understood when the following
detailed description is read with reference to the accompanying
drawings in which like characters represent like parts throughout
the drawings, wherein:
[0009] FIG. 1 is a block diagram of an exemplary computing
device;
[0010] FIG. 2 is a block diagram of a portion of an exemplary wind
turbine control system that include the computing device shown in
FIG. 1;
[0011] FIG. 3 is a schematic view of an exemplary wind turbine that
is regulated through the wind turbine control system shown in FIG.
2;
[0012] FIG. 4 is a schematic view of an exemplary wind turbine park
control system that is used to regulate a plurality of wind
turbines shown in FIG. 3;
[0013] FIG. 5 is a cross-sectional schematic view of a nacelle of
the wind turbine shown in FIG. 3; and
[0014] FIG. 6 is a schematic view of an exemplary method to
generate wind inflow parameters to regulate the operation of the
wind turbine shown in FIG. 3.
[0015] Unless otherwise indicated, the drawings provided herein are
meant to illustrate features of embodiments of this disclosure.
These features are believed to be applicable in a wide variety of
systems comprising one or more embodiments of this disclosure. As
such, the drawings are not meant to include all conventional
features known by those of ordinary skill in the art to be required
for the practice of the embodiments disclosed herein.
DETAILED DESCRIPTION
[0016] In the following specification and the claims, reference
will be made to a number of terms, which shall be defined to have
the following meanings.
[0017] The singular forms "a", "an", and "the" include plural
references unless the context clearly dictates otherwise.
[0018] "Optional" or "optionally" means that the subsequently
described event or circumstance may or may not occur, and that the
description includes instances where the event occurs and instances
where it does not.
[0019] Approximating language, as used herein throughout the
specification and claims, may be applied to modify any quantitative
representation that could permissibly vary without resulting in a
change in the basic function to which it is related. Accordingly, a
value modified by a term or terms, such as "about",
"approximately", and "substantially", are not to be limited to the
precise value specified. In at least some instances, the
approximating language may correspond to the precision of an
instrument for measuring the value. Here and throughout the
specification and claims, range limitations may be combined and/or
interchanged, such ranges are identified and include all the
sub-ranges contained therein unless context or language indicates
otherwise.
[0020] As used herein, the terms "processor" and "computer" and
related terms, e.g., "processing device", "computing device", and
"controller" are not limited to just those integrated circuits
referred to in the art as a computer, but broadly refers to a
microcontroller, a microcomputer, a programmable logic controller
(PLC), an application specific integrated circuit, and other
programmable circuits, and these terms are used interchangeably
herein. In the embodiments described herein, memory may include,
but is not limited to, a computer-readable medium, such as a random
access memory (RAM), and a computer-readable non-volatile medium,
such as flash memory. Alternatively, a floppy disk, a compact
disc-read only memory (CD-ROM), a magneto-optical disk (MOD),
and/or a digital versatile disc (DVD) may also be used. Also, in
the embodiments described herein, additional input channels may be,
but are not limited to, computer peripherals associated with an
operator interface such as a mouse and a keyboard. Alternatively,
other computer peripherals may also be used that may include, for
example, but not be limited to, a scanner. Furthermore, in the
exemplary embodiment, additional output channels may include, but
not be limited to, an operator interface monitor.
[0021] Further, as used herein, the terms "software" and "firmware"
are interchangeable, and include any computer program stored in
memory for execution by personal computers, workstations, clients
and servers.
[0022] As used herein, the term "non-transitory computer-readable
media" is intended to be representative of any tangible
computer-based device implemented in any method or technology for
short-term and long-term storage of information, such as,
computer-readable instructions, data structures, program modules
and sub-modules, or other data in any device. Therefore, the
methods described herein may be encoded as executable instructions
embodied in a tangible, non-transitory, computer readable medium,
including, without limitation, a storage device and/or a memory
device. Such instructions, when executed by a processor, cause the
processor to perform at least a portion of the methods described
herein. Moreover, as used herein, the term "non-transitory
computer-readable media" includes all tangible, computer-readable
media, including, without limitation, non-transitory computer
storage devices, including, without limitation, volatile and
nonvolatile media, and removable and non-removable media such as a
firmware, physical and virtual storage, CD-ROMs, DVDs, and any
other digital source such as a network or the Internet, as well as
yet to be developed digital means, with the sole exception being a
transitory, propagating signal.
[0023] Furthermore, as used herein, the term "real-time" refers to
at least one of the time of occurrence of the associated events,
the time of measurement and collection of predetermined data, the
time to process the data, and the time of a system response to the
events and the environment. In the embodiments described herein,
these activities and events occur substantially
instantaneously.
[0024] The wind turbine control systems described herein provide a
method for estimating real-time wind inflow conditions using
sensors in a fixed frame of a wind turbine to regulate operation of
the wind turbine. Specifically, the embodiments described herein
include a wind turbine control system that is configured to control
the operation of the wind turbine partially using mechanical load
measurements from sensors in a fixed frame of the wind turbine. In
alternative embodiments, the wind turbine control system is further
configured to control the operation of the wind turbine based on
one or more of wind turbine operational data measurements,
atmospheric conditions, and blade pitch angle measurements.
[0025] An exemplary embodiment of the wind turbine control system
for a wind turbine includes at least one mechanical load
measurement sensor, at least one wind turbine regulation device,
and at least one wind observation modeling (WOM) computing device.
The wind turbine includes at least one stationary component. The
mechanical load measurement sensor is coupled to the stationary
component. The WOM computing device is coupled to the mechanical
load measurement sensor and the wind turbine regulation device. The
WOM computing device is configured to receive at least one
mechanical load measurement signal from the mechanical load
measurement sensor. The WOM computing device is configured to
estimate wind inflow conditions using the mechanical load
measurement signal. Based upon the estimated wind inflow
conditions, the WOM computing device is further configured to
generate at least one wind inflow parameter. The WOM computing
device is further configured to generate at least one wind turbine
regulation device command signal based on the wind inflow
parameter. The WOM computing device is further configured to
transmit the wind turbine regulation device command signal to the
wind turbine regulation device to regulate operation of the wind
turbine based upon the wind inflow parameter.
[0026] In some embodiments, the wind turbine control system further
includes at least one blade pitch angle sensor. The WOM computing
device is configured to receive at least one blade pitch angle
signal from the blade pitch angle sensor to generate, with the
mechanical load measurement signal, the at least one wind inflow
parameter. The WOM computing device is further configured to
generate the wind turbine regulation device command signal based on
the wind inflow parameter to transmit to the wind turbine
regulation device.
[0027] In additional embodiments, the wind turbine control system
further includes at least one atmospheric condition measurement
sensor. The WOM computing device is configured to receive at least
one atmospheric condition measurements signal from the atmospheric
condition measurement sensor to generate, with the mechanical load
measurement signal, the at least one wind inflow parameter. The WOM
computing device is further configured to generate the wind turbine
regulation device command signal based on the wind inflow parameter
to transmit to the wind turbine regulation device.
[0028] In still additional embodiments, the wind turbine control
system further includes at least one wind turbine operational data
sensor. The WOM computing device is configured to receive at least
one wind turbine operational data signal from the wind turbine
operational data sensor to generate, with the mechanical load
measurement signal, the at least one wind inflow parameter. The WOM
computing device is further configured to generate the wind turbine
regulation device command signal based on the wind inflow parameter
to transmit to the wind turbine regulation device.
[0029] In the exemplary embodiment, one or more of the mechanical
load measurement signal, the wind turbine operational data signal,
the atmospheric condition measurements signal, or the blade pitch
angle signal are used to generate the at least one wind inflow
parameter.
[0030] FIG. 1 is a block diagram of an exemplary computing device
105 used to facilitate operation of a wind turbine (not shown in
FIG. 1) through a wind turbine control system (not shown in FIG.
1). More specifically, computing device 105 estimates wind inflow
conditions and/or generates a wind observation model based upon
mechanical load measurements, atmospheric condition measurements,
wind turbine operational data measurements, and/or blade pitch
angle measurements. In the exemplary embodiment, computing device
105 is the wind observation modeling (WOM) computing device.
Computing device 105 includes a memory device 110 and a processor
115 operatively coupled to memory device 110 for executing
instructions. In some embodiments, executable instructions are
stored in memory device 110. Computing device 105 is configurable
to perform one or more operations described herein by programming
processor 115. For example, processor 115 may be programmed by
encoding an operation as one or more executable instructions and
providing the executable instructions in memory device 110. In the
exemplary embodiment, memory device 110 is one or more devices that
enable storage and retrieval of information such as executable
instructions and/or other data. Memory device 110 may include one
or more computer readable media.
[0031] Memory device 110 may be configured to store measurements
including, without limitation, atmospheric condition measurements,
wind turbine operational data, mechanical load measurements, blade
pitch angle measurements, and/or any other type data. Also, memory
device 110 includes, without limitation, sufficient data,
algorithms, and commands to facilitate generating physics-based
and/or data-driven models of wind inflow conditions associated with
a wind turbine and use the models to generate wind inflow
parameters to regulate the wind turbine.
[0032] In some embodiments, computing device 105 includes a
presentation interface 120 coupled to processor 115. Presentation
interface 120 presents information, such as a user interface, to a
user 125. In some embodiments, presentation interface 120 includes
one or more display devices and presents measurement data and/or
wind inflow parameters to user 125 using a human machine interface
(HMI) (not shown in FIG. 1). Also, in some embodiments, computing
device 105 includes a user input interface 130. In the exemplary
embodiment, user input interface 130 is coupled to processor 115
and receives input from user 125.
[0033] A communication interface 135 is coupled to processor 115
and is configured to be coupled in communication with one or more
other devices, such as a sensor, a wind turbine control device, or
another computing device 105, and to perform input and output
operations with respect to such devices while performing as an
input channel. Communication interface 135 receives data from
and/or transmits data to one or more remote devices. For example, a
communication interface 135 of one computing device 105 transmits a
signal to the communication interface 135 of another computing
device 105. In some embodiments, communication interface 135 is a
wireless interface.
[0034] Computing device 105 is used to facilitate operation of a
plurality of wind turbines (not shown in FIG. 1) through a wind
turbine park control system (not shown in FIG. 1). In some
embodiments, computing device 105 also includes sufficient
computer-readable/executable instructions, data structures, program
modules, and program sub-modules, to receive other data associated
with measured values from other wind turbines and wind turbine
systems to facilitate overall operation of the wind turbine
park.
[0035] FIG. 2 is a block diagram of a portion of a wind turbine
control system 200 that is used to monitor and control at least a
portion of a wind turbine 300. In some embodiments, wind turbine
control system 200 also includes sufficient
computer-readable/executable instructions, data structures, program
modules, and program sub-modules, to receive other data associated
with measured values from other wind turbine systems to facilitate
overall operation of wind turbine 300. Alternatively, wind turbine
control system 200 is a stand-alone system. Further, alternatively,
wind turbine control system 200 is any computer-based system that
monitors portions of, and generates a wind inflow model for wind
turbine 300. In the exemplary embodiment, wind turbine control
system 200 includes at least one central processing unit (CPU) 215
configured to execute monitoring algorithms and monitoring logic.
CPU 215 is coupled to other devices 220 via a network 225. In some
embodiments, network 225 is a wireless network.
[0036] Referring to FIGS. 1 and 2, CPU 215 is a computing device
105. In the exemplary embodiment, computing device 105 is coupled
to network 225 via communication interface 135. In an alternative
embodiment, CPU 215 is integrated with other devices 220.
[0037] CPU 215 interacts with a first operator 230, e.g., without
limitation, via user input interface 130 and/or presentation
interface 120. In one embodiment, CPU 215 presents information
about wind turbine 300, such as measured blade pitch positions, to
operator 230. Other devices 220 interact with a second operator
235, e.g., without limitation, via user input interface 130 and/or
presentation interface 120. For example, other devices 220 presents
operational information to second operator 235. As used herein, the
term "operator" includes any person in any capacity associated with
operating and maintaining wind turbine 300, including, without
limitation, shift operations personnel, maintenance technicians,
and facility supervisors.
[0038] In the exemplary embodiment, wind turbine 300 includes one
or more monitoring sensors 240 coupled to CPU 215 through at least
one input channel 245. Monitoring sensors 240 collect measurements
including, without limitation, the rotor load measurements and the
blade pitch angle measurements emanating from portions of wind
turbine 300. Monitoring sensors 240 also collect other measurements
including, without limitation, the atmospheric measurements and the
operational data measurements in portions of wind turbine 300.
Monitoring sensors 240 repeatedly, e.g., periodically,
continuously, and/or upon request, transmit measurement readings at
the time of measurement. CPU 215 receives and processes the
measurement readings. Such data is transmitted across network 225
and is accessed by any device capable of accessing network 225
including, without limitation, desktop computers, laptop computers,
and personal digital assistants (PDAs) (neither shown).
[0039] At least one mechanical load measurement sensor 242 (only
one shown in FIG. 2) is located in, within, on, or otherwise
attached to, at least one stationary component of wind turbine 300.
The at least one stationary component may be a flange, a main
bearing, a rotor hub, a rotor shaft, a main bearing housing, and a
yaw bearing, or any means of asymmetric load measurements in a
fixed coordinate system. Mechanical load measurement sensor 242
produces sensor-signals dependent on mechanical load
characteristics of wind turbine 300 that are transmitted to CPU
215. The mechanical load characteristics include, but are not
limited to, bending moments at a rotor shaft, torsional moments at
the rotor shaft, bending moments at a tower top and/or base, and
torsional moments at the tower top and/or base. Mechanical load
measurement sensor 242 repeatedly, e.g., periodically,
continuously, and/or upon request, transmits measurement readings
at the time of measurement. For example, in one embodiment, the set
of measurements are obtained every 0.1 seconds for a time window of
5 seconds. Alternatively, any number of measurements, any interval
time, and any time window are established that enable operation of
wind turbine 300 and wind turbine control system 200 as described
above.
[0040] In some embodiments, a plurality of mechanical load
measurement sensors 242 (only one shown in FIG. 2) measure a set of
mechanical loads. Each mechanical load measurement has a measured
value of a mechanical load characteristic as described above.
[0041] Where the wind turbine is equipped with an individual blade
control mechanism for controlling a pitch angle of each rotor
blade, at least one blade pitch angle measurement is transmitted to
CPU 215 from at least one blade pitch angle sensor 244 (only one
shown in FIG. 2). Blade pitch angle sensor 244 repeatedly, e.g.,
periodically, continuously, and/or upon request, transmits
measurement readings at the time of measurement. Alternatively, any
number of measurements, any interval time, and any time window are
established that enable operation of wind turbine 300 and wind
turbine control system 200 as described above.
[0042] In some embodiments, a plurality of blade pitch angle
sensors 244 (only one shown in FIG. 2) measure a set of blade pitch
angles. Each blade pitch angle measurement has a measured value of
a blade pitch angle as described above.
[0043] CPU 215 is configured to generate per-rotor revolution (nP)
harmonic load components and per-rotor revolution (nP) harmonic
pitch angle components from the mechanical load measurements and
the blade pitch angle measurements. CPU 215 uses the harmonic
components to generate wind flow parameters used to regulate the
wind turbine.
[0044] In the example embodiment, nP harmonic load amplitudes are
computed from the mechanical load measurements via a demodulation
operation at azimuth angle .psi.(t). The following approximation of
a time-varying, almost-periodic load signal .alpha.(t), is given
by
a(t)=a(.psi.(t)).apprxeq.a.sub.k.sup.Ts(.psi.(t) Eq. (1)
where s(.psi.(t)) is a vector of harmonic basis given by
s(.psi.(t))=(1, . . . ,sin(n.psi.(t)),cos(n.psi.(t), . . .
).sup.T,n=(1,N.sub.H) Eq. (2)
where N.sub.H is a higher nP harmonic component contained in the
expression. nP is an n-per-revolution frequency, 1P (i.e., where
n=1) is the fundamental frequency, and 2P, 3P, 4P, and so on, are
harmonics of the fundamental frequency 1P. 0P is 0-per-revolution
frequency. A 0P component of a signal comprises a constant or DC
value over one period. The 0P component of an almost periodic
signal is an average over the demodulation window. A superscript
notation `T` is the vector or matrix transpose operator.
[0045] The harmonic amplitudes over the K-th demodulation window
.psi.(t).epsilon.[.psi..sub.K-2.pi.N.sub.R, .psi..sub.K] are
a.sub.K.sup.T=(a.sub.K.sup.O, . . .
,a.sub.K.sup.n,s,a.sub.K.sup.n,c, . . . ) Eq. (3)
where a.sub.K.sup.O denotes an 0P component, a.sub.K.sup.n s and
a.sub.K.sup.n c denote the sin and cos components of the nP
harmonic frequency, and N.sub.R represent the number of rotor
revolutions over which the load signal .alpha.(t) is measured.
Superscript notation `S` and `C` are shorthand notations for sin
and cos used as superscript to relate the harmonic amplitudes to
its respective harmonic base sin(i.psi.) or cos(i.psi.)
respectively. Subscript notation `K` is the K-th demodulation
window .psi.(t).epsilon.[.psi..sub.K-2.pi.N.sub.R,.psi..sub.K],
K=1, 2, 3, . . . . Constant (0P) and harmonic amplitudes are
computed by projection based on the azimuth angle .psi.(t), such
as,
a K 0 = 1 2 .pi. N R .intg. .psi. K - 2 .pi. N R .psi. K a ( .psi.
) d .psi. Eq . ( 4 ) a K i , s = 1 .pi. N R .intg. .psi. K - 2 .pi.
N R .psi. K a ( .psi. ) sin ( i .psi. ) d .psi. Eq . ( 5 ) a K i ,
c = 1 .pi. N R .intg. .psi. K - 2 .pi. N R .psi. K a ( .psi. ) cos
( i .psi. ) d .psi. Eq . ( 6 ) ##EQU00001##
[0046] In one embodiment, the load signal .alpha.(t) is nodding
moment measurements and/or yawing moment measurements. Nodding and
yawing moments are a particular load measurement on a stationary
component of the wind turbine.
[0047] Where pitch angle measurements are taken in a rotating
frame, Coleman transformations are applied to the load signals to
bring them to a fixed frame to estimate inflow properties defined
in the fixed frame. The Coleman transformation is defined as,
( .beta. d .beta. q .beta. 0 ) = 2 3 [ cos ( n .psi. ) cos ( n (
.psi. + 2 .pi. 3 ) ) cos ( n ( .psi. + 4 .pi. 3 ) ) sin ( n .psi. )
sin ( n ( .psi. + 2 .pi. 3 ) ) sin ( n ( .psi. + 4 .pi. 3 ) ) 1 2 1
2 1 2 ] ( .beta. 1 .beta. 2 .beta. 3 ) Eq . ( 7 ) ##EQU00002##
where .beta..sub.1 . . . 3 are the individual pitch angle signals,
.psi. is the rotor azimuth angle, n represents per-revolution
harmonics to be computed, and .beta..sub.d, .beta..sub.q and
.beta..sub.o are the resulting pitch angle components. In order to
extract the harmonic pitch angle amplitudes, the same demodulation
algorithms shown for load signals are applied to the pitch signals
.beta..sub.d and .beta..sub.q.
[0048] The pitch angle signals are converted from a rotating frame
to a fixed frame because pitch angles are expressed in rotating
frames attached to individual blades. The transformation to the
fixed frame enables a representation of a combined effect of all
rotor blades, not the individual blades, by three quantities
.beta..sub.d, .beta..sub.q, and .beta..sub.0. When the wind turbine
is equipped with individual pitch control, the quantities
.beta..sub.d and .beta..sub.q change the asymmetric loads on the
rotor and therefore complement the load information with regards to
wind inflow.
[0049] The harmonic load amplitudes and the harmonic pitch angle
amplitudes in the stationary frame can be updated at runtime using
the algorithms above.
[0050] In one or more embodiments, the wind turbine control system
200 includes at least one atmospheric condition measurement sensor
246 (only one shown in FIG. 2) configured to measure at least one
atmospheric condition and transfer data associated with the
detected at least one atmospheric condition to CPU 215. Measuring
the at least one atmospheric condition includes, but not limited
to, detecting air density, an ambient air pressure, an ambient air
temperature, an ambient humidity, a rate of rain fall, and/or other
ambient atmospheric conditions using the at least one atmospheric
condition measurement sensor. In the example embodiment, the at
least one atmospheric condition measurement sensor 246 is
positioned on, or in close proximity to, wind turbine 300. The at
least one atmospheric condition measurement sensor 246 repeatedly,
e.g., periodically, continuously, and/or upon request, transmits
measurement readings at the time of measurement. Alternatively, any
number of measurements, any interval time, and any time window are
established that enable operation of wind turbine 300 and wind
turbine control system 200 as described above.
[0051] In some embodiments, a plurality of atmospheric condition
measurement sensors 246 (only one shown in FIG. 2) measure a set of
atmospheric conditions. Each atmospheric condition measurement
point has a measured value of an atmospheric condition described
above.
[0052] In one or more embodiments, wind turbine control system 200
includes at least one operational data sensor 248 (only one shown
in FIG. 2) for measuring at least one operational data point
associated with an operation of wind turbine 300 and transfer data
associated with the detected at least one operational data
measurement to CPU 215. The at least one wind turbine operation
measured by the at least one operational data sensor includes, but
is not limited to, torque on a rotor shaft, power generated by the
wind turbine, rotational speed of the wind turbine, bending stress
values of a rotor shaft, wind direction, wind speed, rotor speed,
output voltage, output current of a turbine generator, turbine
blades pitch angles, rotational speed of a turbine generator, a yaw
of the wind turbine, and power generated by the wind turbine. In
the example embodiment, the at least one operational data sensor
248 is positioned on, or in close proximity to, the wind turbine.
The at least one operational data sensor repeatedly, e.g.,
periodically, continuously, and/or upon request, transmits
measurement readings at the time of measurement. Alternatively, any
number of measurements, any interval time, and any time window are
established that enable operation of wind turbine 300 and wind
turbine control system 200 as described above.
[0053] In some embodiments, a plurality of operational data sensors
248 (only one shown in FIG. 2) measure a set of operational data
points. Each operational data measurement has a measured value of a
wind turbine operation described above.
[0054] In the exemplary embodiment, CPU 215 is configured to
receive at least one mechanical load measurement signal from
mechanical load measurement sensor 242. In additional embodiments,
CPU 215 is further configured to receive at least one wind turbine
operational data signal from wind turbine operational data sensor
248. In further embodiments, CPU 215 is configured to receive at
least one blade pitch angle signal from blade pitch angle sensor
244. In still further embodiments, CPU 215 is configured to receive
at least one atmospheric condition measurement signal from
atmospheric condition measurement sensor 246.
[0055] CPU 215 is further configured to generate, based upon one or
more of the harmonic load components, the harmonic pitch angle
components, the turbine operational data measurements, and the
atmospheric condition measurements, a wind observation model
representing a structure of a wind inflow field acting on the wind
turbine. A structure of the wind observation model may comprise a
static or a dynamical model relating the nP load harmonic
components and the nP pitch angle harmonic components stacked in an
input vector m to wind inflow parameters contained in an output
vector .phi..
x=A(.theta.)x+B.sub.m(.theta.)m+B.sub.q(.theta.)q+d(.theta.) Eq.
(8)
.phi.=C(.theta.)x+D.sub.m(.theta.)m+D.sub.q(.theta.)q+e(.theta.)
Eq. (9)
A yaw rate input q accounts for gyroscopic corrections during a
yawing maneuver. System matrices A, B.sub.m, B.sub.q, C, D.sub.m,
and D.sub.q, are coefficients that depend at least in part on
turbine operational data measurements and/the atmospheric condition
measurements represented by a scheduling vector .theta.. Scheduling
variable .theta. is a vector of quantities representative of
current operating conditions of the wind turbine, which depend in
part on turbine operational data measurements and optionally
atmospheric condition measurements. Vectors d and e are offset
values, also dependent on scheduling variables. A scheduling vector
.theta. can be continuous (i.e. wind speed, rotor speed), discrete
or logical (i.e. if power.gtoreq.nominal power, if individual pitch
control==on).
[0056] Examples of mathematical model formulations utilized for the
wind observation model are, but not limited to, linear parameter
varying systems, neural networks, regression trees, and non-linear
black-box models. The parameters of the wind observation model are
preferably obtained via data-driven system identification, either
from data collected during measurements or from aeroelastic
simulations. The measurements follow standard wind energy practices
similar to the ones adopted in power curve certification.
[0057] Based upon the wind observation model, CPU 215 is configured
to generate real-time estimates of at least one wind inflow
parameter, including, but not limited to, estimates of yaw
misalignment, up-flow, vertical shear, horizontal shear, turbulence
intensity, veer, wind profile, waked state, and non-waked. The wind
observation model estimates the at least one wind inflow parameter
based on the input vector m, as described above.
[0058] CPU 215 is further configured to generate at least one wind
turbine regulation device command signal from the at least one wind
inflow parameter. CPU 215 is further configured to transmit the at
least one wind turbine regulation device command signal to wind
turbine regulation device 250. Wind turbine regulation device 250
is configured to receive the at least one wind turbine regulation
device command signal to regulate operation of wind turbine 300.
Wind turbine regulation device 250 includes, but is not limited to,
a pitch regulator to adjust blade pitch, a torque regulator to
modulate torque in a drive train, a yaw regulator to modify a yaw
position of wind turbine 300, and a mechanical brake regulator to
engage a braking device for the drive train. The wind turbine
regulation device command signal is based upon the at least one
wind inflow parameter. Regulating the operation of wind turbine 300
includes, but is not limited to, controlling the yaw of wind
turbine 300, controlling the pitch of at least one of the turbine
blades (not shown in FIG. 2), controlling the power electronic
converters connected to the turbine generator, controlling the
power generated by wind turbine 300, controlling the rotational
speed of the turbine rotor, and controlling the torque of wind
turbine 300. For example, the wind turbine regulation device
command signal commands the wind turbine regulation device to
change the pitch of one or more rotor blade to enhance the torque
or lower the loads in particular atmospheric conditions.
[0059] In some embodiments, CPU 215 is configured to directly
transmit the wind turbine regulation device command signal to the
wind turbine regulation device to regulate operation of wind
turbine 300.
[0060] Moreover, wind turbine control system 200 described herein
facilitates enhanced control of wind turbine 300 and/or a plurality
of wind turbines 300 in a wind turbine park. Specifically, the
embodiments described herein facilitate enhanced control of the
wind turbine through determinations of real-time, day-to-day, and
seasonal estimates of wind flow in a wind turbine site. As such,
the embodiments described herein facilitate enhancing power
generation performance and increasing annual energy production
(AEP) by taking into account the time-dependent inflow variables
such as wind turbine configuration changes including turbine
outages and blade contamination and erosion.
[0061] FIG. 3 is a schematic view of an exemplary wind turbine 300
that is monitored and controlled through wind turbine control
system 200 (shown in FIG. 2). In the exemplary embodiment, wind
turbine 300 is a horizontal axis wind turbine. Wind turbine 300
includes a tower 302 extending from a supporting surface 304, a
nacelle 306 coupled to tower 302, and a rotor 308 coupled to
nacelle 306. Rotor 308 has a rotatable hub 310 and a plurality of
rotor blades 312 coupled to hub 310. In the exemplary embodiment,
rotor 308 has three rotor blades 312. Alternatively, rotor 308 has
any number of rotor blades 312 that enables wind turbine 300 to
function as described herein. In the exemplary embodiment, tower
302 is fabricated from tubular steel and has a cavity (not shown in
FIG. 3) extending between supporting surface 304 and nacelle 306.
Alternatively, tower 302 is any tower that enables wind turbine 300
to function as described herein including, but not limited to, a
lattice tower. The height of tower 302 is any value that enables
wind turbine 300 to function as described herein.
[0062] Blades 312 are positioned about rotor hub 310 to facilitate
rotating rotor 308, thereby transferring kinetic energy from wind
324 into usable mechanical energy, and subsequently, electrical
energy. Rotor 308 and nacelle 306 are rotated about tower 302 on a
yaw axis 316 to control the perspective of blades 312 with respect
to the direction of wind 324. Blades 312 are mated to hub 310 by
coupling a blade root portion 320 to hub 310 at a plurality of load
transfer regions 322. Load transfer regions 322 have a hub load
transfer region and a blade load transfer region (both not shown in
FIG. 3). Loads induced in blades 312 are transferred to hub 310 via
load transfer regions 322. Each of blades 312 also includes a blade
tip portion 325.
[0063] In the exemplary embodiment, blades 312 have a length
between 50 meters (m) (164 feet (ft)) and 100 m (328 ft), however
these parameters form no limitations to the instant disclosure.
Alternatively, blades 312 have any length that enable wind turbine
to function as described herein. As wind 324 strikes each of blades
312, aerodynamic forces (not shown) are induced on each of blades
312 and rotation of rotor 308 about rotation axis 314 is induced as
blade tip portions 325 are accelerated. A pitch position, or pitch
angle (not shown) of blades 312, i.e., an angle that determines
each of blades' 312 orientation with respect to the rotor plane, is
changed by a pitch adjustment mechanism (not shown in FIG. 3).
Specifically, increasing a pitch angle of blade 312 pitches to
feather.
[0064] Further, in FIG. 3, reference numeral 324 is generally
representative of wind. Since wind 324 is distributed spatially and
temporally, wind speed varies significantly at different points
over the area swept by wind turbine blades 312. Therefore,
different portions of wind turbine 300 experience different wind
speeds. The pitch angles of blades 312 are adjusted about a pitch
axis 318 for each of blades 312. In the exemplary embodiment, the
pitch angles of blades 312 are controlled individually.
Alternatively, blades' 312 pitch is controlled as a group. Still
further alternatively, the pitch of the blades are modulated.
[0065] FIG. 4 is a schematic view of an exemplary wind turbine park
control system 400. In the exemplary embodiment, system 400
includes sensors 240 located proximate to, in, within, on, or
otherwise attached to, at least one stationary component of at
least one wind turbine 300 in wind turbine park 402. System 400
includes wind turbine control system 200. Alternatively, wind
turbine control system 400 is a portion of any other system or
systems regardless of the architecture of wind turbine control
system 200.
[0066] In the exemplary embodiment, wind turbine park control
system 400 includes wind turbine park regulation device 404 and a
plurality of wind turbine regulation devices 250 coupled to wind
turbine park regulation device 404. Sensors 240 are coupled to CPU
215 through a network 406 or data transmission cable 406. Park
regulation device 404 primarily controls each wind turbine 300 in
wind turbine park 402 through wind turbine regulation devices 250
as a function of wind inflow for one or more wind turbines 300
based on analyses by CPU 215, including regulating the angular
rotor speed (revolutions per minute, i.e., rpm) and pitch angles of
blades 312 about pitch axis 318 (both shown in FIG. 3). CPU 215 is
configured to generate and transmit at least one wind turbine
regulation device command signal to park regulation device 404.
Park regulation device 404 transmits the wind turbine regulation
device command signal to regulation devices 250 to regulate
operation of wind turbines 300 in wind turbine park 402.
[0067] In an alternative embodiment, wind turbine park control
system 400 does not include wind turbine park regulation device 404
and CPU 215 communicates directly with wind turbine regulation
devices 250.
[0068] FIG. 5 is a cross-sectional schematic view of nacelle 506 of
exemplary wind turbine 300. Various components of wind turbine 300
are housed in nacelle 506 atop tower 502 of wind turbine 300.
Nacelle 506 includes one pitch drive mechanism 530 that is coupled
to one blade 312 (shown in FIG. 3), where mechanism 530 modulates
the pitch of associated blade 312 along pitch axis 518. In the
exemplary embodiment, the pitch drive mechanism 530 includes at
least one pitch drive motor 531.
[0069] Nacelle 506 also includes a rotor 508 that is rotatably
coupled to an electric generator 532 positioned within nacelle 506
via rotor shaft 534, a gearbox 536, a high speed shaft 538, and a
coupling 540. Rotation of shaft 534 rotatably drives gearbox 536
that subsequently rotatably drives shaft 538. Shaft 538 rotatably
drives generator 532 via coupling 540 and shaft 538 rotation
facilitates generator 532 production of electrical power. Gearbox
536 and generator 532 are supported by supports 542 and 544,
respectively. In the exemplary embodiment, gearbox 536 utilizes a
dual path geometry to drive high speed shaft 538. Alternatively,
main rotor shaft 534 is coupled directly to generator 532 via
coupling 540.
[0070] Nacelle 506 further includes a yaw adjustment mechanism 546
that is used to rotate nacelle 506 and rotor 508 on an axis to
control the perspective of blades 312 with respect to the direction
of the wind. Nacelle 506 also includes at least one meteorological
mast 548, where mast 548 includes a wind vane and anemometer. Mast
548 provides information to a turbine control system (not shown)
that includes wind direction and/or wind speed.
[0071] A portion of the turbine control system resides within a
control panel 550. Nacelle 506 further includes forward and aft
support bearings 552 and 554, respectively, where bearings 552 and
554 facilitate radial support and alignment of shaft 534.
[0072] Wind turbine 300 includes a pitch control system 560, where
at least a portion of pitch control system 560 is positioned in
nacelle 506, or alternatively, outside nacelle 506. Specifically,
at least a portion of pitch control system 560 described herein
includes at least one wind turbine regulation device, i.e.,
processor 562 and a memory device (not shown), and at least one
input/output (I/O) conduit 564, where conduit 564 includes at least
one I/O channel (not shown). More specifically, processor 562 is
positioned within control panel 550. In some embodiments, processor
562 is substantially similar to, or includes, processor 115 (shown
in FIG. 1).
[0073] Processor 562 and other processors (not shown) as described
herein process information transmitted from a plurality of
electrical and electronic devices that includes, but not be limited
to, blade pitch position feedback devices 566 (described further
below) and electric power generation feedback devices (not shown).
RAM and storage devices (not shown) store and transfer information
and instructions to be executed by processor 562. RAM and storage
devices can also be used to store and provide temporary variables,
static (i.e., non-changing) information and instructions, or other
intermediate information to processor 562 during execution of
instructions by processor 562. Instructions that are executed
include, but are not limited to, resident blade pitch system
control commands. The execution of sequences of instructions is not
limited to any specific combination of hardware circuitry and
software instructions.
[0074] In the exemplary embodiment, at least a portion of pitch
control system 560 including, but not limited to, processor 562 is
positioned within control panel 550. Moreover, processor 562 is
coupled to blade pitch drive motors 531 via at least one I/O
conduit 564. I/O conduit 564 includes any number of channels having
any architecture including, but not limited to, Cat 5/6 cable,
twisted pair wiring, and wireless communication features. Pitch
control system 560 includes distributed and/or centralized control
architectures, or any combination thereof
[0075] Pitch control system 560 also includes a plurality of
independent blade pitch position feedback devices 566 coupled with
processor 562 via at least one I/O conduit 564. In the exemplary
embodiment, each pitch drive mechanism 530 is associated with a
single blade pitch position feedback device 566 (also known as a
blade pitch position device or a position feedback device).
Alternatively, any number of blade pitch position feedback devices
566 are associated with each mechanism 530. Therefore, in the
exemplary embodiment, mechanism 530 and associated drive motor 531,
as well as device 566, are included in system 560 as described
herein. Each blade pitch position feedback device 566 measures a
pitch position of each blade 312 with respect to rotor hub 510.
Blade pitch position feedback device 566 is any suitable sensor
having any suitable location within or remote to wind turbine 300,
such as, but not limited to, optical angle encoders, magnetic
rotary encoders, and incremental encoders, or some combination
thereof. Moreover, blade pitch position feedback device 566
transmits pitch measurement signals (not shown) that are
substantially representative of associated blade 312 pitch position
to processor 562 for processing thereof.
[0076] FIG. 6 is a schematic view of generating wind inflow
parameters 620 using a wind observation model 618. Monitoring
sensors on exemplary wind turbine 300 transmit rotor load
measurement sensor signals 602 and blade pitch angle measurement
sensor signals 604 to the WOM (wind observation modeling) computing
device (not shown). Rotor load measurements and blade pitch angle
measurements are processed (signal processing 606), as explained
above, into nP load components 610 and nP blade pitch angle
components 608.
[0077] Atmospheric condition measurements 614 and turbine
operational data measurements 616 are also transmitted to the WOM
computing device. The WOM computing device uses one or more of
atmospheric condition measurements 614, turbine operational data
measurements 616, nP load components 610, and nP blade pitch angle
components 608 to generate wind observation model 618. The WOM
computing device uses the wind observation model to generate wind
inflow parameters 620. The WOM computing device transmits a command
signal, based upon wind inflow parameters 620, to the wind turbine
regulation device (not shown) to regulate the wind turbine.
[0078] The above described wind turbine control system for a wind
turbine includes at least one mechanical load measurement sensor,
at least one wind turbine regulation device, and at least one wind
observation modeling (WOM) computing device. The wind turbine
includes at least one stationary component. The mechanical load
measurement sensor is coupled to the stationary component. The WOM
computing device is coupled to the mechanical load measurement
sensor and the wind turbine regulation device. The WOM computing
device is configured to receive at least one mechanical load
measurement signal from the mechanical load measurement sensor. The
WOM computing device is configured to generate at least one wind
inflow parameter using the mechanical load measurement signal. The
WOM computing device is further configured to generate at least one
wind turbine regulation device command signal based on the wind
inflow parameter. The WOM computing device is still further
configured to transmit the wind turbine regulation device command
signal to the wind turbine regulation device to regulate operation
of the wind turbine based upon the wind inflow parameter.
[0079] An exemplary technical effect of the methods, systems, and
apparatus described herein includes at least one of: (a) real-time
knowledge of the inflow conditions on a wind turbine site is used
in control strategies for one or more of the following: enhancing
power generation performance, increasing annual energy production
(AEP), reducing mechanical loads, and reducing noise; (b)
increasing the accuracy in predicting the power performance, loads
and noise of wind turbines under different inflow conditions; (c)
predicting turbine wake length and strength more accurately,
enabling better wind farm control; and (d) enabling enhanced
discrimination between disturbed and non-disturbed sound pressures
facilitates using smaller margins to regulatory parameters, thereby
further enhancing power generation.
[0080] Exemplary embodiments of methods and systems for monitoring
and controlling wind turbines are not limited to the specific
embodiments described herein, but rather, components of systems
and/or steps of the methods may be utilized independently and
separately from other components and/or steps described herein. For
example, the methods may also be used in combination with other
wind turbine systems requiring in-situ recognition of wind inflow
conditions and are not limited to practice with only the wind
turbines and methods as described herein. Rather, the exemplary
embodiment can be implemented and utilized in connection with many
other applications, equipment, and systems that may benefit from
physics-based modeling and control in an operating environment with
wind inflow conditions.
[0081] Although specific features of various embodiments of the
disclosure may be shown in some drawings and not in others, this is
for convenience only. In accordance with the principles of the
disclosure, any feature of a drawing may be referenced and/or
claimed in combination with any feature of any other drawing.
[0082] Some embodiments involve the use of one or more electronic
or computing devices. Such devices typically include a processor or
controller, such as a general purpose central processing unit
(CPU), a graphics processing unit (GPU), a microcontroller, a
reduced instruction set computer (RISC) processor, an application
specific integrated circuit (ASIC), a programmable logic circuit
(PLC), and/or any other circuit or processor capable of executing
the functions described herein. The methods described herein may be
encoded as executable instructions embodied in a computer readable
medium, including, without limitation, a storage device and/or a
memory device. Such instructions, when executed by a processor,
cause the processor to perform at least a portion of the methods
described herein. The above examples are exemplary only, and thus
are not intended to limit in any way the definition and/or meaning
of the term processor.
[0083] This written description uses examples to disclose the
embodiments, including the best mode, and also to enable any person
skilled in the art to practice the embodiments, including making
and using any devices or systems and performing any incorporated
methods. The patentable scope of the disclosure is defined by the
claims, and may include other examples that occur to those skilled
in the art. Such other examples are intended to be within the scope
of the claims if they have structural elements that do not differ
from the literal language of the claims, or if they include
equivalent structural elements with insubstantial differences from
the literal language of the claims.
* * * * *